ML_Sales_Prediction

An ML model that predicts sales across multiple stores belonging to Rossmann Pharmaceuticals. The stores are spread across several cities. The prediction is made six weeks ahead of time and it is delivered to analysts in the finance team. Factors that are necessary for predicting the sales across the various stores include:

1. Promotions
2. Competitions
3. School and state holidays
4. Seasonality
5. Locality

REPO Structure

1. Notebooks folder -> EDA Notebook file
2. Data folder -> CSV data files
3. Tests folder -> Test scripts
4. Scripts -> Python scripts including a dashboard file
5. .dvc -> DVC config files Workflows are created using CML

Installation guide

git clone https://github.com/KaydeeJR/ML_Sales_Prediction

pip install -r requirements.txt

ML workflow diagram